Change Reqest | Custom cost function

[KarazhovAndrii]

Hello DTAI Team,

thank you for sharing this great project.
Consider in subsequent releases a possibility for users to define cost function, as they could need different metrics to evaluate the distance when computing DTW. Example of the interface (dist_func optional parameter is added):

def distance(s1, s2, dist_func=None,
             window=None, max_dist=None, max_step=None,
             max_length_diff=None, penalty=None, psi=None,
             use_c=False, use_pruning=False, only_ub=False)
def warping_paths(s1, s2, dist_func=None, window=None, max_dist=None, use_pruning=False,
                  max_step=None, max_length_diff=None, penalty=None, psi=None, psi_neg=True,
                  use_c=False, use_ndim=False):

where dist_func suppose to have a signature:

def dist_func(a, b):
    return some_computation_over_a_b

[wannesm]

We would need to support this also in the C code to be consistent. While not necessarily difficult to add in one location, it requires changes at multiple locations (e.g. also in the bounds) and increases the cost of maintaining. So we will have to think about how to do this consistent throughout the codebase (we already have this a bit to support ndim series).

If you urgently need this. It is not too difficult to change this in the python part (no compilation required). Simply change these two lines in the code:

dtaidistance/dtaidistance/dtw.py

Line 289 in 054e97e

d = (s1[i] - s2[j])**2

dtaidistance/dtaidistance/dtw.py

Line 409 in 054e97e

if use_ndim:

[wannesm]

In the master branch, this functionality is now available by using the inner_dist argument. When using the pure Python implementation, this can be any callable function (wrapped in an object that has as callable arguments inner_dist and result). When using the the fast dtw computation in C this needs to be one of 'euclidean' or 'squared euclidean'.